Synthesis and Evaluation of [18F]FEtLos and [18F]AMBF3Los as Novel 18F-Labelled Losartan Derivatives for Molecular Imaging of Angiotensin II Type 1 Receptors
Bibliographic record
Abstract
Losartan is widely used in clinics to treat cardiovascular related diseases by selectively blocking the angiotensin II type 1 receptors (AT1Rs), which regulate the renin-angiotensin system (RAS). Therefore, monitoring the physiological and pathological biodistribution of AT1R using positron emission tomography (PET) might be a valuable tool to assess the functionality of RAS. Herein, we describe the synthesis and characterization of two novel losartan derivatives PET tracers, [18F]fluoroethyl-losartan ([18F]FEtLos) and [18F]ammoniomethyltrifluoroborate-losartan ([18F]AMBF3Los). [18F]FEtLos was radiolabeled by 18F-fluoroalkylation of losartan potassium using the prosthetic group 2-[18F]fluoroethyl tosylate; whereas [18F]AMBF3Los was prepared following an one-step 18F-19F isotopic exchange reaction, in an overall yield of 2.7 ± 0.9% and 11 ± 4%, respectively, with high radiochemical purity (>95%). Binding competition assays in AT1R-expressing membranes showed that AMBF3Los presented an almost equivalent binding affinity (Ki 7.9 nM) as the cold reference Losartan (Ki 1.5 nM), unlike FEtLos (Ki 2000 nM). In vitro and in vivo assays showed that [18F]AMBF3Los displayed a good binding affinity for AT1R-overexpressing CHO cells and was able to specifically bind to renal AT1R. Hence, our data demonstrate [18F]AMBF3Los as a new tool for PET imaging of AT1R with possible applications for the diagnosis of cardiovascular, inflammatory and cancer diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".